Mining online peer support communities to understand treatment side effects in Multiple Sclerosis
Year: 2026
Type: article
Abstract: Online peer-support forums provide valuable insights into how people living with Multiple Sclerosis (MS) experience and interpret treatment-related side effects. While clinical literature documents the physiological profiles of these effects, less is known about their emotional framing in patient-generated discourse. This study analysed discussions from the r/MultipleSclerosis subreddit to examine patterns of engagement, sentiment, and emotional expression across four treatment categories: Disease-Modifying Therapies (DMTs), Treatments for MS Attacks, Symptom-Management Medicines, and "Other treatments". Sentiment analysis was conducted using VADER, and emotional profiling was performed using the NRC Emotion Lexicon, followed by statistical comparisons across categories. DMT-related side effects accounted for 74% of discussions. Although engagement levels did not significantly differ across treatment types, negative sentiment predominated. Emotional analyses revealed significantly higher levels of anger and disgust in DMT-related posts, while fear was prevalent across all categories. These findings highlight the emotional burden associated with long-term MS therapies and demonstrate the potential of online patient discourse as a complementary source of insight into treatment experiences and patient-centred care. Implications for practice and future directions are discussed.
Author: Bernard Ayine
Institution: Hong Kong Polytechnic University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
OpenAlex ID: W7160270010